Particle Deposition Model Research Articles

Can we use viral receptor mapping and particle deposition models to predict the clinical severity of novel airborne pathogens?

Can we use viral receptor mapping and particle deposition models to predict the clinical severity of novel airborne pathogens?

Machine learning-enhanced stochastic uncertainty and sensitivity analysis of the ICRP human respiratory tract model for an inhaled radionuclide

The International Commission on Radiological Protection (ICRP) has developed the reference Human Respiratory Tract Model (HRTM), detailed in ICRP Publications 66 and 130, to estimate the deposition and clearance of inhaled radionuclides. These models utilize reference anatomical and physiological parameters for particle deposition (PD). Biokinetic models further estimate retention and excretion of internalized particulates, aiding the derivation of inhalation dose coefficients (DC). This study aimed to assess variability in deterministic131I biokinetic and dosimetry models through stochastic analysis using the updated HRTM from ICRP Publication 130. The complexities of the ICRP PD model were reconstructed into a new, independent computational model. Comparison with reference data for total PD fractions for reference worker, solely a nose breather, covering activity median aerodynamic diameters from 0.3μm to 20μm, showed a 1.04% relative and 0.7% absolute difference, demonstrating good agreement with ICRP deposition fractions. The deterministic DC module was reconstructed in Python and expanded for stochastic analysis, systematically expanding deposition components from HRTM and assigning probability distribution functions to uncertain parameters. These were integrated into an in-house stochastic radiological exposure dose calculator, utilizing latin hypercube sampling. A case of an occupational radionuclide intake was explored, in which biodistribution and committed effective DC (CEDC) were computed for131I type F, considering a lognormal particle size distribution with a median of 5μm. Results showed the published ICRP reference CEDC marginally exceeds the 75th percentile of observed samples, with log-gamma distribution as the best-fit probability distribution. A Random Forest regression model with SHapley Additive exPlanations was employed for sensitivity analysis to predict feature importance. The analysis identified the HRTM particle transport rates scaling factor, followed by the aerodynamic deposition efficiency in the alveolar interstitial region as the most impactful parameters. This study offers a unique stochastic approach on inhaled particulate metabolism, enhancing radiation consequence management, medical countermeasures, and dose reconstruction for epidemiological studies.

Numerical modeling of particle deposition in a realistic respiratory airway using CFD-DPM and genetic algorithm.

In this study, a realistic model of the respiratory tract obtained from CT medical images was used to solve the flow field and particle motion using the Eulerian-Lagrangian approach to obtain the maximum particle deposition in the bronchial tree for the main purpose of optimizing the performance of drug delivery devices. The effects of different parameters, including particle diameter, particle shape factor, and air velocity, on the airflow field and particle deposition pattern in different zones of the lung were investigated. In addition, a genetic algorithm was employed to obtain the maximum particle deposition in the bronchial tree and the effect of the aforementioned parameters on particle deposition. Reverse flow, vortex formation, and laryngeal jet all affect the airflow structure and particle deposition pattern. The mouth-throat region had the highest deposition fraction at various flow rates. A change in the deposition pattern with an increased deposition fraction in the throat was observed owing to the increased diameter and shape factor of the particles, resulting from the higher inertia and drag force, respectively. The particle deposition analysis showed that three parameters, shape factor, diameter, and velocity, are directly related to particle deposition, and the diameter is the most effective parameter for particle deposition, with an effect of 60% compared to the shape factor and velocity. Finally, the prediction of the genetic algorithm reported a maximum particle deposition in the bronchial tree of 17%, whereas, based on the numerical results, the maximum particle deposition was reported to be 16%. Therefore, there is a 1% difference between the prediction of the genetic algorithm and the numerical results, which indicates the high accuracy of the prediction of the genetic algorithm.

Study of the behavior of dust particles in helium turbines considering the effects of particle deposition and resuspension

The deposition of graphite dust poses significant challenges to the helium turbines in high-temperature gas-cooled reactors. In this study, FLUENT, a Computational Fluid Dynamics (CFD) program was used with a discrete-phase model and a random-walk model to calculate the trajectories of particles (assumed spherical). Considering the interactions between particles and the wall as well as the resuspension effect of the fluid, a particle-deposition model was established and coupled to the flow-field calculations of blades with film cooling using user-defined functions. The influence of different deposition models, particle diameters, and blowing ratios on deposition were investigated. The results show rebounding and resuspending particles significantly affect the particle-deposition rate and its distribution. With increasing particle diameter, the deposition rate initially increases and then decreases. The influence of blowing ratio on deposition is complex; as the blowing ratio is increased, the deposition rate of small particles increases, while that of large particles decreases.

Ash fouling characteristic analysis and prediction for pillow plate heat exchanger in waste heat recovery based on attentive-feature decision algorithm

Ash fouling on heat exchanger surfaces in waste heat recovery and utilization is an inevitable result of solid fuel combustion and particle deposition, affecting the efficiency, availability and operating cost of an energy utilization system. Fouling prediction plays a critical role in reasonable design and efficient operation of heat exchangers. However, credible monitoring and accurate prognostic towards fouling condition always remain a challenge, largely due to the complex flue gas component and abominable service environment of heat exchangers. In this paper, a novel ash fouling prediction method combined with Effective Particle Size Filtering and Multistep Attentive-Feature Decision algorithm (EF-MAFD) for Pillow Plate Heat Exchanger (PPHE) is proposed. First, a numerical fouling model with Discrete Phase Model (DPM) combined particle deposition and removal model is developed. Validation work is conducted on Nusselt number, pressure drop coefficient and normal restitution coefficient with existing experimental data. The effect of geometrical configuration of PPHE and condition on the fouling characteristic is then evaluated with this model. Next, the EF-MAFD ash fouling prediction model is established, in which the initial particle size distribution is transformed into an effective diameter innovatively and two indicators evaluating the fouling state, namely critical fouling resistance and critical fouling time are defined and predicted. The results indicate that fouling mainly occurs downstream of the welding spots and shows an asymptotic growing trend over time. PPHE with smaller diameter of welding spot, channel height and pitch ratio possess anti-fouling potential. In comparison to existing methods, the newly developed EF-MAFD method has the capacity to deal effectively with the complex particle distribution and provides the most satisfying prediction ability with coefficient of determination (R2) of 0.93 and mean absolute prediction error (MAPE) of 7.8 %. The proposed method could be utilized as a reliable tool to support fouling condition-based maintenance and design for various types of heat exchangers operating in fly ash conditions.

Modelling Drug Delivery to the Small Airways: Optimization Using Response Surface Methodology

AimThe aim of this in silico study was to investigate the effect of particle size, flow rate, and tidal volume on drug targeting to small airways in patients with mild COPD.MethodDesign of Experiments (DoE) was used with an in silico whole lung particle deposition model for bolus administration to investigate whether controlling inhalation can improve drug delivery to the small conducting airways. The range of particle aerodynamic diameters studied was 0.4 – 10 µm for flow rates between 100 – 2000 mL/s (i.e., low to very high), and tidal volumes between 40 – 1500 mL.ResultsThe model accurately predicted the relationship between independent variables and lung deposition, as confirmed by comparison with published experimental data. It was found that large particles (~ 5 µm) require very low flow rate (~ 100 mL/s) and very small tidal volume (~ 110 mL) to target small conducting airways, whereas fine particles (~ 2 µm) achieve drug targeting in the region at a relatively higher flow rate (~ 500 mL/s) and similar tidal volume (~ 110 mL).ConclusionThe simulation results indicated that controlling tidal volume and flow rate can achieve targeted delivery to the small airways (i.e., > 50% of emitted dose was predicted to deposit in the small airways), and the optimal parameters depend on the particle size. It is hoped that this finding could provide a means of improving drug targeting to the small conducting airways and improve prognosis in COPD management.

Oxidative potential associated with reactive oxygen species of size-resolved particles: The important role of the specific sources

Oxidative potential (OP) is a predictor of particulate matter (PM) toxicity. Size-resolved PM and its components that influence OP values can be generated from several sources. However, There is little research have attempted to determine the PM toxicity generated from specific sources. This paper studied the OP characterization and reactive oxygen species (ROS) formation of particles from specific sources and their effects on human health. OP associated with ROS of size-resolved particles was analyzed by using dithiothreitol (DTT) method and electron paramagnetic resonance (EPR) spectroscopy technology. And OP and ROS deposition of specific source PM were calculated for health through the Multi-path particle deposition (MPPD) model. The results evidenced that the highest water-soluble OP (OPws) from traffic sources (OPm: 104.50 nmol min−1·ug−1; OPv: 160.15 nmol min−1·m−3) and the lowest from ocean sources (OPm: 22.25 nmol⋅min−1⋅ug−1; OPv: 54.16 nmol min−1·m−3). The OPws allocation in PM from different sources all have a unimodal pattern range from 0.4 to 3.2 μm. ROS (·OH) displayed the uniform trend as PM OPws, indicating that PM< 3.2 is the major contributor to adverse health impacts for size-resolved PM because of its enhanced oxidative activity compared with PM> 3.2. Furthermore, this study predicted the DTT consumption of PM were assigned to different components. Most DTT losses are attributed to the transition metals. For specific sources, transition metals dominates DTT losses, accounting for 38%–80% of DTT losses from different sources, followed by Hulis-C, accounting for 1%–10%. MPPD model calculates that over 66% of pulmonary DTT loss comes by PM< 3.2, and over 71% of pulmonary ROS generation from PM< 3.2. Among these sources of pollution, traffic emissions are the primary contributors to reactive oxygen species (ROS) in environmental particulate matter (PM). Therefore, emphasis should be placed on controlling traffic emissions, especially in coastal areas.

Simulation of Hydrate Migration and Deposition in Pipe with Diameter Reduction and Direction Variation

Summary Pipes with diameter reduction and direction variation are very common in deepwater extraction. While the high-pressure and low-temperature conditions may trigger severe hydrate problems, current studies on hydrate particle migration and deposition are mainly carried out in pipes with a constant diameter, whereas the law of diameter reduction has been less explored; in particular, the effect of diameter reduction + direction variation in pipe has not been reported. In this study, a model of hydrate particle migration and deposition in special pipelines is established based on the computational fluid dynamics (CFD)-discrete element solver (DEM)-application programming interface (API) method, which can be used to carry out real-time visualization calculations of hydrate particles. Simultaneously, this paper reveals the mechanism of hydrate particle migration and deposition at the diameter reduction and direction variation, which provides a new idea for the design of the pipe. Furthermore, for the pipe with diameter reduction + direction variation, the entire process of deposition blockage is simulated, and dangerous locations of pipe clogging are identified. The simulation results found that there is a maximum hydrate deposition particle diameter (MHDPD) for hydrate deposition in the pipe. The results of this work may provide valuable references for accurate prediction of particle deposition in deepwater development.

Numerical simulations on film cooling performance of turbine blade before and after particles deposition

In the present study, a C3X turbine blade with film holes is selected to investigate the effect of blowing ratio on particle deposition and heat transfer characteristics on the blade surface. The deposition characteristics of the blade surface are obtained based on the EI⁃Batsh particle deposition model, and the surface morphology of the deposited layer is reproduced using the dynamic mesh model. The results show that the particle deposition mainly occurs at the leading edge and pressure surface of the blade, but the large-size particles will be deposited on the suction surface due to rebound. The effect of blowing ratio on large-size particles is more obvious, and the deposition rate tends to decrease and then increase with the increase of blowing ratio. Within the range of blowing ratios in this paper, particle deposition leads to an improvement in the cooling efficiency of the air film in the pressure surface along the flow direction near the air film hole region, but a significant decrease in the cooling efficiency near the trailing edge region. Overall, particle deposition caused an increase in overall blade temperature.

Effective density of inhaled environmental and engineered nanoparticles and its impact on the lung deposition and dosimetry

BackgroundAirborne environmental and engineered nanoparticles (NPs) are inhaled and deposited in the respiratory system. The inhaled dose of such NPs and their deposition location in the lung determines their impact on health. When calculating NP deposition using particle inhalation models, a common approach is to use the bulk material density, ρb, rather than the effective density, ρeff. This neglects though the porous agglomerate structure of NPs and may result in a significant error of their lung-deposited dose and location.ResultsHere, the deposition of various environmental NPs (aircraft and diesel black carbon, wood smoke) and engineered NPs (silica, zirconia) in the respiratory system of humans and mice is calculated using the Multiple-Path Particle Dosimetry model accounting for their realistic structure and effective density. This is done by measuring the NP ρeff which was found to be up to one order of magnitude smaller than ρb. Accounting for the realistic ρeff of NPs reduces their deposited mass in the pulmonary region of the respiratory system up to a factor of two in both human and mouse models. Neglecting the ρeff of NPs does not alter significantly the distribution of the deposited mass fractions in the human or mouse respiratory tract that are obtained by normalizing the mass deposited at the head, tracheobronchial and pulmonary regions by the total deposited mass. Finally, the total deposited mass fraction derived this way is in excellent agreement with those measured in human studies for diesel black carbon.ConclusionsThe doses of inhaled NPs are overestimated by inhalation particle deposition models when the ρb is used instead of the real-world effective density which can vary significantly due to the porous agglomerate structure of NPs. So the use of realistic ρeff, which can be measured as described here, is essential to determine the lung deposition and dosimetry of inhaled NPs and their impact on public health.Graphical abstract

Modeling particle deposition in the primary circuit of pressurized water reactors for the OSCAR code

Particulate corrosion products are generated in the primary system of pressurized water reactors (PWRs) by volume precipitation and by erosion of oxides formed on metal surfaces through their uniform corrosion. The activation of corrosion products, mainly 58Co and 60Co (respectively coming from the activation of 58Ni and 59Co) leads to radiation field growth around the primary system, directly impacting system integrity and the radioprotection of nuclear workers. In order to understand and mitigate contamination by activated corrosion products, contamination predictions can be performed using the OSCAR code, which relies on the development of models to describe the numerous and complex interactions at stake. Particulate corrosion products account for a significant portion of corrosion products, as such the deposition/erosion mechanisms have their importance for the overall computation of surface or volume contamination. The aim of this article is to present an updated and inclusive deposition model for particulate corrosion products by taking into account surface interactions. The impact of the new deposition model on contamination predictions is then evaluated and has enabled to reproduce, for the first time using the OSCAR code, the preferential contamination in 58Co in the cold side of the circuit, measured by gamma spectrometry with the EMECC device on commercially PWRs.

Numerical simulation of unsteady magneto hydrodynamic flow of nanoparticle deposition in the porous alveolar ducts

This study aims to investigate a numerical model of dust particle deposition in the human lung. There were significant discrepancies in deposition inside each alveolate duct and between ducts of a given generation, indicating that the mean acinar concentration can be greatly exceeded by limited particle concentrations. During expiration, the huge particles try to exit the construction but are failed. The similarity transformation is used to describe the differential equations controlling the flow. The various systematic quantities, such as the fluid velocity, and dust particle velocity are determined. In this research, non-linear governing coupled partial differential equations are explained by developing a finite-difference method established on the Crank-Nicolson model that is accurate, precise, widely validated, and unconditionally stable. The technique’s precision and efficacy are proven. To show how various physical factors affect the velocity and temperature profiles, various numerical data are collected and visually displayed. For each of the characteristics tested, the results show that the nano particles’ velocity is higher in comparison to the fluid particles.

Characteristics of Coal Dust Deposition in Boiler Tail Gas Pipelines

Coal dust deposition in boiler tail gas pipelines can significantly affect boilers’ thermal and energy efficiency. This study investigates the deposition characteristics of coal dust particles in boiler tail gas tubes in variable cross-section tubes. Numerical simulations were performed using the Reynolds Stress Model and the Discrete Particle Model. User-defined functions coding is used to construct the particle deposition model in the particle deposition model. The study analyses the distribution of turbulent kinetic energy locations in the gradient tube, compares the distribution of particle deposition on its wall, and concludes that the deposition distribution of coal dust particles in the gradient tube is slightly different for different particle sizes. Smaller particles have a higher deposition efficiency in equal cross-section pipes than larger particles. Particle size also has a significant effect on pipe taper and expansion. The results of this study can provide theoretical guidance for optimising the design of boiler tail gas pipelines, improving energy efficiency, and reducing environmental pollution.

Characteristics of Coal Dust Deposition in Boiler Tail Gas Pipelines

Coal dust deposition in boiler tail gas pipelines can significantly affect boilers’ thermal and energy efficiency. This study investigates the deposition characteristics of coal dust particles in boiler tail gas tubes in variable cross-section tubes. Numerical simulations were performed using the Reynolds Stress Model and the Discrete Particle Model. User-defined functions coding is used to construct the particle deposition model in the particle deposition model. The study analyses the distribution of turbulent kinetic energy locations in the gradient tube, compares the distribution of particle deposition on its wall, and concludes that the deposition distribution of coal dust particles in the gradient tube is slightly different for different particle sizes. Smaller particles have a higher deposition efficiency in equal cross-section pipes than larger particles. Particle size also has a significant effect on pipe taper and expansion. The results of this study can provide theoretical guidance for optimising the design of boiler tail gas pipelines, improving energy efficiency, and reducing environmental pollution.

Simulation of Hydrate Particles Aggregation and Deposition in Gas-Dominated Flow

Summary Owing to low-temperature and high-pressure production environments, hydrate generation, accumulation, and deposition are prone to occur in deepwater oil and gas production wells and transportation pipelines, leading to pipeline blockage and threatening the safety of oil and gas production. To explore the aggregation mechanism and deposition law of hydrate particles in the main gas diversion pipeline, this study considered the adhesion effect of hydrate particles and established a hydrate particle aggregation and deposition model based on theory and experiments. The coupled computational fluid dynamics-discrete element method (CFD-DEM) is used in the simulation calculation. The simulation results were compared with the relevant experimental results, and maximum and average errors of 9.48% and 4.56% were observed, respectively. It was found that the main factor affecting the aggregation of hydrates is the adhesion between particles. As the subcooling temperature increased, the aggregation and adhesion of the hydrate particles increased to varying degrees. The tangential adhesion force between the hydrate aggregate particles was significantly greater than the normal adhesion force, and the adhesion force between the particles gradually increased from the surface to the interior of the aggregates. The coordination number of the hydrate particles can quantitatively characterize the degree of aggregation and is affected by many factors, such as adhesion. By studying the particle coordination number, the evolution of hydrate accumulation and deposition under different conditions can be summarized. Based on the simulation results, the mathematical relationship between different dimensionless numbers and hydrate deposition ratio (HDR) was calculated, and an expression that can predict the HDR was obtained, with an average relative error of 10.155%. This study provides a theoretical basis for predicting the aggregation and deposition of hydrate particles in gas-dominated systems and a reference for the development of hydrate prevention and control plans.

Effect of Nanoparticles Deposition on Cooling Performance of Photovoltaic Panels

Abstract The current research aims to investigate the deposition and dispersion of nanoparticles for thermally developing laminar flow inside a cooling channel of a photovoltaic (PV) panel. The particle transport is modeled in an Eulerian-Lagrangian framework using a two-way coupling approach to perform the particle trajectories. In the absence of turbulent fluctuations, Brownian diffusion is the main force that contributes to particles deposition due to the small size of the particles used in the current study (below 100 nm). Several parameters were investigated such as inlet temperature, Reynolds number, nanoparticle size, and concentration in order to record the subsequent effects on the deposition efficiency, heat transfer coefficient, and pressure drop. There is no direct particle deposition model available in commercial computational packages such as Fluent, so a deposition model was developed and programmed in C-language using the User-Defined Functions (UDF) capabilities available in the Fluent solver to model how the particles are affected by wall impacts. Model validation was performed against the experimental studies found in the literature and showed good agreement. The efficiency of particle deposition on the channel wall was found to increase with decreasing nanoparticle size and/or Reynolds number. Furthermore, the deposition efficiency increased with the increase in fluid inlet temperature and nanofluid concentration. Moreover, the heat transfer rate was decreased as a result of decreasing nanofluid concentration caused by nanoparticle deposition on the channel walls, while the pumping power was also decreased due to concentration loss.

Particle Deposition Characteristics on Turbine Blade Surface Based on Critical Velocity Model

Based on the critical velocity model of EI-Batsh, this paper further considered the particle deposition-bounce and the secondary collision deposition after the bounced, which improved the original particle deposition model. Then the particle deposition mass per unit of time and area (PDM) was proposed to characterize the particle deposition on the turbine blade surface. The effects of different rows of cooling film holes, blowing ratios, particle diameters and diameters of cooling film holes on the particle deposition characteristics of the blade surface were then investigated. The results show that the deposition amount of the single cooling film holes opening with radial inclination facing the leading edge is the smallest, and the deposition amount gradually increases when the inclination angle is shifted toward the pressure and suction surface. As the blowing ratio increases from 0.3 to 1.5, the amount of particle deposition tends to decrease and then increase, and reaches a minimum value when the blowing ratio is about 0.5. The deposition increases with increasing particle diameters in the range of 2-10 μm and gradually increases when the diameter of cooling film holes is from 0.99 mm to 1.5 mm.

Particle deposition model for a fully developed turbulent channel flow

This study aims to develop a mathematical model for solid particle deposition under a fully-developed turbulent flow in a rectangular channel, considering the effect of the change in geometry over time. The present study introduces a mathematical approach to predict the equilibrium thickness/mass of the deposition, saturation and equilibrium times, and their corresponding non-dimensionalized parameters. Scaling analysis, and parametric study are reported. For a fixed Reynolds number Re, the particle deposition increases with non-dimensional relaxation time. In general, as more particles are deposited, the surface takes less time to become saturated and approach equilibrium faster. The saturation and equilibrium times decrease with an increase in non-dimensional particle relaxation time. For a fixed particle concentration, as the inlet velocity increases, the saturation and equilibrium time decreases, and the asymptotic deposited mass decreases.

A numerical analysis of ash fouling characteristics in elliptical tube bundles

Ash fouling in flue gas heat exchangers (FGHE) detrimentally affects waste heat recovery systems' performance and efficiency by impeding heat transfer, increasing operational resistance, and escalating maintenance costs. The main purpose of this study is to develop an improved particle deposition model for predicting ash fouling characteristics and to explore the fouling reduction performance of elliptical tube bundles (ETB) at various system parameters. The findings reveal that ETB can efficiently reduce operation resistance and ash fouling in FGHE with an insignificant loss in heat exchanger efficiency, especially at large eccentricities (E) and/or low flue gas velocity (vinlet). The most cost-effective E is 0.78, which decreases ash deposit and pressure drop by 66.4% and 48.4%, respectively, at the expense of a 14.2% Nusselt number reduction at vinlet = 10 m/s. Ash fouling reveals three distinctive hotspots: Hotspot 1 located approximately at ±30°, Hotspot 2 at the flow stagnation area, and Hotspot 3 roughly at ±150°. The deposit layer thickness at these hotspots varies between rows and with the E, vinlet and particle diameter (dp). The layer thickness at the flow stagnation regions increases with any of the E, vinlet, and dp. The study also found that medium-sized particles (dp = 5 μm) are the easiest to deposit on tube surfaces, followed by large particles (dp = 10 μm). Small particles (dp = 1 μm) are the least likely to deposit due to their small inertia. Medium-sized and large particles deposit primarily at the windward side of the tubes, while small particles tend to deposit more on the leeward side as they can be easily drawn into the recirculation zones behind those tubes. Increasing the E would significantly alleviate fouling by medium-sized and large particles but does not significantly change the ash fouling situation of small particles.

Numerical analysis of catalyst particle deposition characteristics in a flue gas turbine with an improved particle motion and deposition model

To more accurately understand and predict the deposition behavior of catalyst particles in the flue gas turbine cascade, test and numerical combined study is performed in this paper. Based on the systematic analysis of the deposition process and physical mechanism of the catalyst particles, the traditional DRW model, critical velocity particle deposition model and removal model were corrected with the user defined function custom function and validated with the actual deposition morphology. On this basis, the effects of the particle Stokes number and flue gas parameters on the particle deposition characteristics of the flue gas turbine cascade were detailed investigated. The results show that the revised DRW model, critical velocity and removal model can more accurately predict the deposition location and deposition rate of particles in the turbine cascade. With the increase in the Stokes number of particles, the average particle impact rate on the blade surface gradually increased, while the average deposition rate showed a trend of first increasing and then decreasing. The average deposition rate of particles in the rotor blade surface is roughly twice as high as that in the stator surface. With the increase of the flue gas expansion ratio, the deposition rate of particles less than 3 μm gradually increases, while the deposition rate of particles greater than 3 μm tends to decrease. In addition, the change in the flue gas expansion ratio has no obvious effect on the particle deposition distribution in different size ranges.